Sandstone aggregate mine carbon emission statistical accounting model and method

Abstract

The invention relates to the technical field of carbon emission statistical accounting, in particular to a carbon emission statistical accounting model and method for a gravel aggregate mine. The invention provides a carbon emission statistical accounting model specially aiming at the gravel aggregate mine, and the carbon emission condition of the mine can be accurately reflected. Through automatic data collection and calculation, the efficiency and accuracy of carbon emission statistical accounting are improved. The carbon emission management capability of a mine enterprise is enhanced, and an effective emission reduction strategy can be formulated.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission statistical accounting, and in particular to a carbon emission statistical accounting model and method for sand and gravel aggregate mines. Background Art

[0002] As the global climate change problem becomes increasingly serious, governments and international organizations have taken measures to reduce greenhouse gas emissions. The statistics and accounting of carbon emissions are the basic work to achieve this goal. It not only helps the government to formulate and adjust emission reduction policies, but also enables enterprises to better manage their environmental impact and improve their competitiveness in the market.

[0003] Among many industries, infrastructure construction is one of the main sources of global carbon emissions. As an indispensable raw material in infrastructure construction, the production and processing of sand and gravel aggregates involve a large amount of energy consumption and raw material use, which generates significant carbon emissions. According to statistics, the carbon emissions of the global sand and gravel aggregate industry account for a considerable part of the global total emissions, so it is particularly important to accurately calculate the carbon emissions of this industry.

[0004] However, the production process of sand and gravel aggregate mines has its own particularity, including open-pit mining, crushing, screening and transportation, and the carbon emission sources of these links are complex and scattered. Traditional carbon emission statistical accounting methods often use unified emission factors and calculation models, which are difficult to accurately reflect the actual emissions of sand and gravel aggregate mines. In addition, these methods may not fully consider factors such as the specific operating conditions, technical level and raw material characteristics of the mine, resulting in deviations in the accounting results.

[0005] In order to improve the accuracy and reliability of carbon emission statistics and accounting, it is necessary to develop carbon emission statistics and accounting models and methods specifically for sand and gravel aggregate mines. These models and methods need to be able to calculate more accurate carbon emissions based on the specific production data and operating conditions of the mines. At the same time, these models and methods should also be able to adapt to the ever-changing production environment and technological advances to ensure the continuous updating and improvement of carbon emission data. Summary of the invention

[0006] In order to overcome the above technical problems, the first technical solution of the present application discloses a statistical accounting model for carbon emissions from sand and gravel aggregate mines, including:

[0007] Data collection module: responsible for collecting activity data of the target sand and gravel aggregate mine production process;

[0008] Carbon emission calculation module: Combines mine emission factors and activity data to calculate the carbon emissions of target mines;

[0009] Data review module: review the calculation results;

[0010] Report generation module: Generates a statistical accounting report on mine carbon emissions based on the audited data.

[0011] Furthermore, the data collection module includes:

[0012] Data collection: The data collection includes online data entry system and automated data import system;

[0013] Data storage and management: Use the central database to quickly query, mine, backup and restore data;

[0014] Data quality control: used to regularly review, verify and check the collected data.

[0015] Furthermore, the carbon emission calculation module includes:

[0016] Emission factor library construction: Based on the specific operations of the mine, the carbon emission factors covering all processes of the mine production activities are constructed;

[0017] Carbon emission calculation: Calculate the mine’s direct and indirect carbon emissions based on activity data and emission factors according to the carbon emission algorithm;

[0018] Data verification and quality control: used to verify the rationality and accuracy of data;

[0019] Result output and report: used to generate detailed carbon emissions report.

[0020] Furthermore, the data review module includes:

[0021] Data verification: used to verify whether the obtained data is reasonable;

[0022] Outlier monitoring: used to identify outliers in data and analyze the causes;

[0023] Data quality scoring: used to score the accuracy, completeness, consistency and timeliness of data for further verification or correction;

[0024] Report Generation: Used to generate audit reports.

[0025] Furthermore, the model also includes a user interaction interface for users to input data or modify or verify data.

[0026] And, the application of the above accounting model in the statistical accounting of carbon emissions from sand and gravel aggregate mines.

[0027] The second technical solution of the present application discloses a method for statistical accounting of sand and gravel aggregate mine emissions, comprising the following steps:

[0028] The mine emission factors and activity data are input according to the production process of the target sand and gravel aggregate mine for calculation, and the calculation results are reviewed and then a data report is generated.

[0029] The beneficial effects of this application are as follows: a carbon emission statistical accounting model specifically for sand and gravel aggregate mines is provided, which can accurately reflect the carbon emission situation of the mines. Through automated data collection and calculation, the efficiency and accuracy of carbon emission statistical accounting are improved. The carbon emission management capabilities of mining enterprises are enhanced, which helps to formulate effective emission reduction strategies. DETAILED DESCRIPTION

[0030] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0031] Unless otherwise specifically stated, the relative arrangement of the parts and steps set forth in these embodiments, numerical expressions and numerical values ​​do not limit the scope of the application. The technology, method and equipment known to those of ordinary skill in the relevant art may not be discussed in detail, but in appropriate cases, the technology, method and equipment should be considered as a part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values.

[0032] Unless otherwise specified, the meanings of the technical terms in this specification are the same as those generally understood by those skilled in the art. However, if there is any conflict, the definitions in this specification shall prevail.

[0033] The first implementation mode of the present application discloses a statistical accounting model for carbon emissions from sand and gravel aggregate mines, including:

[0034] Data collection module: responsible for collecting activity data of the target sand and gravel aggregate mine production process;

[0035] Carbon emission calculation module: Combines mine emission factors and activity data to calculate the carbon emissions of target mines;

[0036] Data review module: review the calculation results;

[0037] Report generation module: Generates a statistical accounting report on mine carbon emissions based on the audited data.

[0038] In this embodiment, the data collection module collects activity data related to carbon emissions in various processes in the mining production process, such as energy consumption data, raw material consumption data, transportation data, etc. In the production process of sand and gravel aggregate mines, the activity data related to carbon emissions covers multiple aspects, such as:

[0039] S1. Energy consumption data: Electricity consumption: The amount of electricity consumed by mining, crushing, screening and other equipment, measured in kilowatt-hours (kWh). For example, if a jaw crusher runs for 500 hours in a month with a power of 100 kilowatts, the electricity consumption of the crusher in that month is 50,000 kWh.

[0040] Fuel consumption: includes diesel, gasoline and other fuels used for transport vehicles, loaders, drilling rigs and other equipment, usually in liters (L) or cubic meters (m 3 ). For example, a transport truck in a mine consumes 2,000 liters of diesel per month.

[0041] S2. Raw material consumption data: Ore mining volume: Record the amount of sand and gravel aggregate ore mined from the mine in tons (t). This reflects the scale of production, because the larger the mining volume, the higher the energy consumption and carbon emissions in the subsequent processing. For example, a mine mined 100,000 tons of ore in a quarter.

[0042] Auxiliary material consumption: the amount of auxiliary materials used in the mining and processing process, such as explosives and lubricants. The amount of explosives used (kg) is related to the intensity of the mining operation, while the consumption of lubricants (liters) is related to the operation and maintenance of the equipment. For example, a blasting operation uses 500 kg of explosives, and a piece of equipment consumes 20 liters of lubricants per month.

[0043] S3. Transportation data: Transportation mileage: The mileage of transportation vehicles in transporting raw materials or finished sand and gravel aggregates within and outside the mine, in kilometers (km). It is used to calculate energy consumption and carbon emissions during transportation. For example, a transportation fleet has a cumulative mileage of 50,000 kilometers in one month.

[0044] Transport trips: Records the number of round trips of transport vehicles, reflecting the frequency of transport activities. The more transport trips there are, the higher the energy consumption and carbon emissions will be. For example, within a month, vehicles on a certain transport route make 1,000 round trips.

[0045] Vehicle load: refers to the weight of sand and gravel aggregates actually loaded on each transport vehicle, measured in tons (t). Vehicle load affects transportation efficiency and energy consumption, and heavier loads may require more fuel consumption. For example, a truck transports 20 tons of sand and gravel aggregates at one time.

[0046] The data collection module in this application collects these detailed activity data, which can more comprehensively and accurately calculate the carbon emissions of sand and gravel aggregate mines, providing a reliable basis for subsequent carbon emission management and emission reduction strategy formulation.

[0047] In a further embodiment, after collecting the detailed activity data in the production process of the above-mentioned sand and gravel aggregate mine, it is necessary to import data in the data collection module, preferably, including online data input and automatic data import. The online data input system is input by the user through the user interaction interface, and the automatic data import system can be used to import files in multiple data formats (such as CSV, Excel, JSON) from the mine's automation equipment and systems (such as energy management systems, production monitoring systems, etc.), and at the same time, by designing data mapping and conversion rules, ensure that the data imported from different sources can be correctly implied into the data structure required by the carbon emission accounting model.

[0048] In this embodiment, the data mapping and conversion rules are key mechanisms to ensure that the data imported from different sources can be correctly integrated into the carbon emission accounting model. Some specific rules are provided below.

[0049] S1. Data format uniform rules

[0050] Field format specification: For date fields, the format is uniformly specified as "YYYY-MM-DD" to ensure that all date data can be accurately identified and processed when imported. For example, the equipment operation date "2023 / 05 / 10" recorded in the energy management system needs to be converted to the format of "2023-05-10" when imported.

[0051] Numerical precision setting: For energy consumption data (such as electricity, fuel, etc.), it is required to retain two decimal places. For example, if the electricity data recorded in the energy management system is "1234.5678", it should be converted to "1234.57" when imported.

[0052] S2. Data content mapping rules

[0053] Equipment name correspondence: Map the equipment number or name recorded in the production monitoring system with the equipment name defined in the carbon emission accounting model. For example, the crusher with the equipment number "001" in the production monitoring system corresponds to the equipment name "Jaw Crusher No. 1" in the model. By establishing a mapping relationship, it is ensured that the data can be accurately associated with the carbon emission calculation of the corresponding equipment.

[0054] Energy type classification: Unify the energy types in data from different sources and classify them. For example, in the energy usage recorded by automation equipment, different expressions such as "gasoline", "92# gasoline", and "Gasoline" are mapped to the "gasoline" category in the carbon emission accounting model to accurately calculate the carbon emissions corresponding to energy consumption.

[0055] S3. Data time scale conversion rules

[0056] Time period aggregation: If the production monitoring system records equipment operation data by minute, but the carbon emission accounting model uses hours as the calculation unit, the minute-level data needs to be aggregated by hour. For example, the power consumption data of the equipment within 60 minutes is summed up to obtain the power consumption data per hour to meet the time scale requirements of the model.

[0057] Data timestamp alignment: Ensure that the timestamps of data from different systems are consistent in order to facilitate time series analysis. For example, if the timestamps recorded by the energy management system are accurate to seconds, while the timestamps recorded by the production monitoring system are accurate to minutes, the timestamps need to be unified to the minute level or appropriate interpolation processing needs to be performed so that the data can accurately correspond in the time dimension.

[0058] S4. Rules for handling missing values ​​and outliers

[0059] Missing value filling: For missing values ​​in certain key data fields, formulate reasonable filling strategies. For example, if the load information of some trains in the transportation data is missing, it can be filled according to the average load or historical data of the vehicle type to ensure the integrity of the data, and the filling situation can be recorded in the report for subsequent analysis.

[0060] Identification and correction of outliers: Set the judgment criteria for outliers, such as determining the normal range of a certain type of data (such as the normal range of equipment operating power) based on historical data, and data outside this range is considered an outlier. For the identified outliers, further verify the cause, and if it is a data entry error, correct it; if it is a real abnormal situation (such as a sudden equipment failure causing a sharp increase in energy consumption), mark it in the data and explain it in detail in the audit report so that special treatment can be performed in carbon emission calculation and analysis.

[0061] S5. Data association and integration rules

[0062] Process association: The data of different links are associated and integrated according to the sand and gravel aggregate production process. For example, the energy consumption data of the mining link is associated with the amount of ore mined, and the equipment operation data of the crushing link is associated with the output of crushed sand and gravel, so as to ensure that the relationship between the production activities and carbon emissions of each link can be accurately reflected when calculating carbon emissions.

[0063] Merge multiple data sources: When importing data from multiple automation systems, merge them according to the business logic and time sequence of the data. For example, if both the energy management system and the production monitoring system record the equipment operation time, the relevant data in the two systems need to be merged into a complete equipment operation time sequence according to the time logic of equipment start and stop, to avoid data duplication or omission, and provide comprehensive data support for accurate calculation of carbon emissions.

[0064] These rules need to be customized and optimized according to the actual situation of the mine and the specific requirements of the carbon emission accounting model to ensure the accuracy, completeness and consistency of the data, so as to achieve reliable carbon emission statistical accounting.

[0065] Data storage and management: Use the central database to quickly query, mine, backup and restore data;

[0066] Data quality control: used to regularly review, verify and check the collected data.

[0067] Furthermore, the carbon emission calculation module includes:

[0068] Construction of emission factor library: Based on the specific operations of the mine, a carbon emission factor covering all processes of the mine's production activities is constructed; it includes carbon emission factors for various activities of the mine, such as energy consumption, raw material processing, transportation, etc. At the same time, the emission factors are regularly updated with the latest scientific research and statistical data to reflect the impact of technological progress and operational changes on carbon emissions.

[0069] In this embodiment, the carbon emission factor is the carbon emission amount in terms of carbon emissions of each activity consumed in the mine production process collected by the data collection module. These emission factors are a bridge that connects different production activities with carbon emissions, and are used to convert the collected activity data into corresponding carbon emissions. For example, the carbon emission factor in the mining process of each ton of ore, the carbon emission factor when each liter of diesel is burned for transportation, etc., are determined, so as to calculate the carbon emissions of each link by multiplying the activity data by the emission factor. It provides a unified quantitative standard for the carbon emission calculation of different mines, making the carbon emission calculation results of different mines comparable.

[0070] Carbon emission calculation: According to the carbon emission algorithm, the direct and indirect carbon emissions of the mine are calculated based on activity data and emission factors; the algorithm can process multiple data inputs, including energy consumption, raw material usage, product output, waste generation, etc., and calculate the corresponding carbon emissions based on these data. At the same time, the algorithm also takes into account the temporal changes in carbon emissions, such as seasonal production fluctuations, equipment maintenance cycles, etc., to provide more accurate carbon emission forecasts.

[0071] This embodiment specifically describes the carbon emission algorithm.

[0072] S1. Direct carbon emissions calculation

[0073] Energy consumption and carbon emissions calculation

[0074] 1. Regarding power consumption:

[0075] First, determine the source of electricity (such as thermal power generation, hydropower generation, wind power generation, etc.), because the emission factors of electricity from different sources vary greatly. Assume that the electricity obtained from the power grid has an emission factor of EF elec (Unit: kg CO2 equivalent / kWh), the power consumption of the mine in a certain period is E elec (Unit: kilowatt-hour).

[0076] Then the direct carbon emissions from electricity consumption are:

[0077] C elec =E elec ×EF elec

[0078] 2. For fuel consumption (taking diesel as an example):

[0079] The emission factor of diesel is set as EF diesel = (unit: kg CO2 equivalent / liter), the diesel consumption during this period is V diesel (Unit: liter).

[0080] Direct carbon emissions from diesel consumption C diesel =V diesel ×EF diesel .

[0081] 3. The calculation method of carbon emissions from other energy sources (such as gasoline, natural gas, etc.) is similar. The direct carbon emissions generated by various energy consumption are added together to obtain the total direct carbon emissions from energy consumption C directenergy =∑ i C i (i represents different energy types).

[0082] S2. Calculation of indirect carbon emissions

[0083] 1. Calculation of carbon emissions from raw material processing

[0084] For ore mining and processing

[0085] The emission factor for ore mining and processing is EF ore (Unit: kg CO2 equivalent / ton of ore), the amount of ore mined and processed in a certain period of time is M ore (Unit: tons).

[0086] The indirect carbon emissions from ore mining and processing are Core =M ore ×EF ore .

[0087] 2. For auxiliary materials (such as explosives, lubricants, etc.)

[0088] The emission factor for explosives is EF explosive (Unit: kg CO2 equivalent / kg explosive), the amount of explosives used during this period is M explosive (Unit: kg), then the indirect carbon emissions generated by the use of explosives C explosive =M explosive ×EF explosive .

[0089] The emission factor for lubricating oil is EF lubricant (Unit: kg CO2 equivalent / L lubricant), the lubricant usage is V lubricant (Unit: liter), then the indirect carbon emissions generated by the use of lubricating oil C lubricant =V lubricant ×EF lubricant .

[0090] 3. Total indirect carbon emissions from raw material processing C indirectmaterial =∑ j C j (j represents different raw material types).

[0091] 4. Calculation of transportation carbon emissions

[0092] The calculation of carbon emissions in the transportation process is relatively complicated and requires consideration of factors such as transportation method, transportation distance, and vehicle load.

[0093] For road transport (taking truck as an example):

[0094] First determine the truck emission factor EF truck (Unit: kg CO2 equivalent / ton-km), the weight of the cargo transported in a certain period is W truck (Unit: tons), transportation mileage is D truck (Unit: km).

[0095] The indirect carbon emissions from road transport are C truck =W truck ×D truck ×EF truck .

[0096] If there are other modes of transportation (such as railways, water transport, etc.), similar calculations are performed according to their corresponding emission factors and transportation-related data. The total indirect carbon emissions generated by transportation are C indirecttrasport =∑ k C k(k represents different modes of transportation).

[0097] 5. Calculation of carbon emissions from waste treatment (if any)

[0098] For the treatment of tailings, waste rock and other wastes:

[0099] The emission factor for tailings disposal is EF tailings (Unit: kg CO2 equivalent / ton of tailings), the amount of tailings generated in a certain period is M tailings (Unit: tons), then the indirect carbon emissions from tailings treatment are C tailings =M tailings ×EF tailings .

[0100] The emission factor for waste rock treatment is EF wasterock (Unit: kg CO2 equivalent / ton waste rock), the amount of waste rock produced is M wasterock (Unit: tons), then the indirect carbon emissions from waste rock treatment are C wasterock =M wasterock ×EF wasterock .

[0101] Total indirect carbon emissions from waste treatment C indirectwaste =∑ l C l (l represents different waste types).

[0102] S3. Consider the time series changes of carbon emissions

[0103] 1. Adjustment for seasonal production fluctuations

[0104] Establish a seasonal emission adjustment coefficient model. For example, by analyzing historical data, it is found that in summer, due to high temperatures, the heat dissipation demand of equipment increases, energy consumption increases, and the emission coefficient may be 1:1; in winter, the energy consumption of equipment startup is high, and the emission coefficient is 1.2; in spring and autumn, the emission coefficient is 1.0. Suppose the emission adjustment coefficient of the current season is K season .

[0105] The adjusted direct carbon emissions C directadjusted =C directenergy ×K season , adjusted indirect carbon emissions C indirectadjusted =(C indirectmaterial +C indirecttransport +C indirectwaste )×K season .

[0106] 2. Adjustment of equipment maintenance cycle

[0107] During equipment maintenance, the equipment operating efficiency is reduced or some equipment stops operating, and the emission is reduced. Suppose the emission adjustment factor during equipment maintenance is K maintenance (For example, if the emission during maintenance is 50% of normal, then K maintenance =0.5).

[0108] According to the equipment maintenance plan, determine the adjusted direct carbon emissions C during the maintenance period directadjustedmaintenance =C directenergy ×K maintenance , adjusted indirect carbon emissions C indirectadjustedmaintenance =(C indirectenergy +C indirecttransport +C indirectwaste )×K maintenance .

[0109] For non-maintenance periods, emissions calculations remain unchanged.

[0110] S4. Final carbon emission calculation results

[0111] Total carbon emissions from mines C total =C directadjusted +C indirectadjusted (adjusted for seasonal fluctuations) or C total =C directadjustedmaintenance +C indirectadjustedmaintenance (Consider equipment maintenance cycle adjustment).

[0112] The algorithm calculates direct and indirect carbon emissions through detailed classification and makes adjustments based on time-series change factors. It can more accurately calculate the carbon emissions of sand and gravel aggregate mines, providing reliable data support for the carbon emission management and emission reduction strategy formulation of mines. At the same time, emission factors need to be regularly updated based on the latest scientific research and actual conditions to ensure the accuracy and timeliness of the calculation results.

[0113] Data verification and quality control: used to check the rationality and accuracy of data, which is achieved by embedding data verification mechanism in the calculation process;

[0114] It should be noted that the carbon emission calculation module is modular in design, which allows for easy customization and expansion according to the specific needs of different mines. It also facilitates maintenance and updating, and can quickly adapt to changes in emission factors or calculation methods when these changes occur.

[0115] Result output and report: used to generate detailed carbon emission reports, such as carbon emission calculation results displayed in the form of icons and reports, which are convenient for users to understand and analyze. At the same time, this step also provides a report generation tool, allowing users to generate detailed carbon emission reports as needed, including information such as emissions, emission factors, activity data and calculation methods.

[0116] Furthermore, the data review module includes:

[0117] Data validation: used to verify whether the obtained data is reasonable. This step specifies a set of detailed data validation rules, including data range, data type, data format and logical consistency. The validation rules may include whether the energy consumption data is within a reasonable range, whether the date and time stamp are correct, and whether the logical relationship between different data points is consistent.

[0118] Outlier detection: used to identify outliers in data and analyze the causes; for example, automatically identify outliers in data, such as data points that suddenly increase or decrease, which may be caused by measurement errors, data entry errors, or abnormal time in the actual production process. At the same time, outlier detection can also use statistical methods, such as standard deviation analysis, box plot analysis, or anomaly detection algorithms based on machine learning.

[0119] Data quality scoring: used to score the accuracy, completeness, consistency and timeliness of data for further verification or correction;

[0120] Report Generation: Used to generate audit reports.

[0121] Furthermore, the model also includes a user interaction interface for users to input data or modify or verify data.

[0122] Example 1: Carbon emission calculation method for a specific mining area and related activities

[0123] step1. Determine the accounting scope: clarify the specific mining areas and related activities covered by this accounting.

[0124] Step 2. Identify emission sources: for example, energy consumption during mining (such as diesel for machinery and equipment), raw material processing, etc.

[0125] Step 3. Collect activity data:

[0126] Record the diesel consumption used for mechanical equipment over a certain period of time, e.g. [specific value] litres.

[0127] Step 4. Select emission factor: According to the type of diesel, select the corresponding emission factor, assuming it is 3.15tCO2e / t (tCO2e means carbon dioxide equivalent).

[0128] Step 5. Calculate carbon emissions:

[0129] Formula used: Carbon emissions (tCO2e) = emission factor (tCO2e / t) × emissions (t)

[0130] Calculation process: Carbon emissions = 3.15 × (diesel consumption ÷ diesel density), diesel density can be obtained by referring to relevant information.

[0131] Step 6. Data verification and review:

[0132] Check the accuracy of diesel consumption records by comparing and verifying with equipment operation records, refueling records, etc.

[0133] Ensure that the selection of emission factors complies with relevant standards and actual conditions.

[0134] Step 7. Summary and Report:

[0135] Calculation results: The carbon emissions generated by diesel consumption in mining activities are [specific calculation results] tCO2e.

[0136] The generated report may include: basic information of the mine, such as name, location, etc.

[0137] Accounting time period.

[0138] List in detail each emission source and the corresponding activity data, emission factors and carbon emissions.

[0139] Description of the calculation method and basis.

[0140] The process and results of data verification and review.

[0141] There may also be analysis and recommendations on carbon emissions.

[0142] Please note that this is just a simple example. Actual mining activities may be more complex, involving the collection and calculation of multiple emission sources and activity data. In actual operations, relevant standards and methods must be strictly followed to ensure the accuracy and reliability of the data. At the same time, it is also necessary to select appropriate carbon emission calculation methods according to specific circumstances, such as direct emission calculation method, indirect emission calculation method, mass balance method or actual measurement method.

[0143] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A statistical accounting model for carbon emissions from sand and gravel aggregate mines, characterized in that: include: Data collection module: responsible for collecting activity data of the target sand and gravel aggregate mine production process; Carbon emission calculation module: Combines mine emission factors and activity data to calculate the carbon emissions of target mines; Data review module: review the calculation results; Report generation module: Generates a statistical accounting report on mine carbon emissions based on the audited data.

2. The calculation model according to claim 1, characterized in that: The data collection module comprises: Data collection: The data collection includes online data entry system and automated data import system; Data storage and management: Use the central database to quickly query, mine, backup and restore data; Data quality control: used to regularly review, verify and check the collected data.

3. The calculation model according to claim 1, characterized in that: The carbon emission calculation module includes: Emission factor library construction: Based on the specific operations of the mine, the carbon emission factors covering all processes of the mine production activities are constructed; Carbon emission calculation: Calculate the mine’s direct and indirect carbon emissions based on activity data and emission factors according to the carbon emission algorithm; Data verification and quality control: used to verify the rationality and accuracy of data; Result output and report: used to generate detailed carbon emissions report.

4. The calculation model according to claim 1, characterized in that: The data review module includes: Data verification: used to verify whether the obtained data is reasonable; Outlier monitoring: used to identify outliers in data and analyze the causes; Data quality scoring: used to score the accuracy, completeness, consistency and timeliness of data for further verification or correction; Report Generation: Used to generate audit reports.

5. The calculation model according to claim 1, characterized in that: The model also includes a user interaction interface for users to input data or modify and check data.

6. Application of the calculation model according to any one of claims 1 to 5 in the statistical calculation of carbon emissions in sand and gravel aggregate mines.

7. A method for calculating the statistical accounting of sand and gravel aggregate mine emissions, using the accounting model as described in any one of claims 1 to 5, characterized in that: The method includes the following steps: inputting the mine emission factor and activity data according to the production process of the target sand and gravel aggregate mine for calculation, and generating a data report after data review of the calculation results.